Supporting the collaborative decision-making process in an automotive supply chain with a multi-agent system

Abstract

Collaborative initiatives such as collaborative design, collaborative planning and forecasting, and open collective innovation are increasingly accepted as approaches that can effectively support decision-making (DM) processes in a range of different industries. However, justifying and demonstrating the benefits of collaborative solutions remains a challenge and has been under-researched. Demonstrating the feasibility of implementing collaborative solutions as opposed to traditional, linear and transactional solutions is even less evident. The purpose of this paper is to conceive a collaborative solution that supports the multi-level DM process in a real, tree-based automotive supply chain environment. The hypothesis presented posits that by sharing information collaboratively, improvements in terms of the profit and service levels will be found within the supply chain and at every supply chain node.

Keywords:

• collaborative decision-making
• decision support systems
• supply chain management
• automotive industry
• multi-agent systems

Acknowledgements

The authors thanks the support from the project ‘Operations Design and Management in Global Supply Chains (GLOBOP)’ (Ref. DPI2012-38061-C02-01), funded by the Ministry of Science and Education of Spain, for the supply chain environment research contribution. In addition, we thank the EWG-DSS and their four expert anonymous referees as well as the guest editorial board for their useful suggestions and criticism on earlier versions of this paper.